Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System
People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users i...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Avvenuti, Marco [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: BIG-OH: BInarization of gradient orientation histograms - Baber, Junaid ELSEVIER, 2014transfer abstract, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:67 ; year:2020 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.pmcj.2020.101225 |
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| 520 | |a People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. | ||
| 520 | |a People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. | ||
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| 700 | 1 | |a Cresci, Stefano |4 oth | |
| 700 | 1 | |a Nizzoli, Leonardo |4 oth | |
| 700 | 1 | |a Tesconi, Maurizio |4 oth | |
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10.1016/j.pmcj.2020.101225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001139.pica (DE-627)ELV051293811 (ELSEVIER)S1574-1192(20)30081-X DE-627 ger DE-627 rakwb eng 004 VZ Avvenuti, Marco verfasserin aut Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. Human-as-a-sensor Elsevier Hybrid sensing Elsevier Emergency management Elsevier Artificial intelligence Elsevier Online social networks Elsevier Bellomo, Salvatore oth Cresci, Stefano oth Nizzoli, Leonardo oth Tesconi, Maurizio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:67 year:2020 pages:0 https://doi.org/10.1016/j.pmcj.2020.101225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 67 2020 0 |
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10.1016/j.pmcj.2020.101225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001139.pica (DE-627)ELV051293811 (ELSEVIER)S1574-1192(20)30081-X DE-627 ger DE-627 rakwb eng 004 VZ Avvenuti, Marco verfasserin aut Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. Human-as-a-sensor Elsevier Hybrid sensing Elsevier Emergency management Elsevier Artificial intelligence Elsevier Online social networks Elsevier Bellomo, Salvatore oth Cresci, Stefano oth Nizzoli, Leonardo oth Tesconi, Maurizio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:67 year:2020 pages:0 https://doi.org/10.1016/j.pmcj.2020.101225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 67 2020 0 |
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10.1016/j.pmcj.2020.101225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001139.pica (DE-627)ELV051293811 (ELSEVIER)S1574-1192(20)30081-X DE-627 ger DE-627 rakwb eng 004 VZ Avvenuti, Marco verfasserin aut Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. Human-as-a-sensor Elsevier Hybrid sensing Elsevier Emergency management Elsevier Artificial intelligence Elsevier Online social networks Elsevier Bellomo, Salvatore oth Cresci, Stefano oth Nizzoli, Leonardo oth Tesconi, Maurizio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:67 year:2020 pages:0 https://doi.org/10.1016/j.pmcj.2020.101225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 67 2020 0 |
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10.1016/j.pmcj.2020.101225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001139.pica (DE-627)ELV051293811 (ELSEVIER)S1574-1192(20)30081-X DE-627 ger DE-627 rakwb eng 004 VZ Avvenuti, Marco verfasserin aut Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. Human-as-a-sensor Elsevier Hybrid sensing Elsevier Emergency management Elsevier Artificial intelligence Elsevier Online social networks Elsevier Bellomo, Salvatore oth Cresci, Stefano oth Nizzoli, Leonardo oth Tesconi, Maurizio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:67 year:2020 pages:0 https://doi.org/10.1016/j.pmcj.2020.101225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 67 2020 0 |
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10.1016/j.pmcj.2020.101225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001139.pica (DE-627)ELV051293811 (ELSEVIER)S1574-1192(20)30081-X DE-627 ger DE-627 rakwb eng 004 VZ Avvenuti, Marco verfasserin aut Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. Human-as-a-sensor Elsevier Hybrid sensing Elsevier Emergency management Elsevier Artificial intelligence Elsevier Online social networks Elsevier Bellomo, Salvatore oth Cresci, Stefano oth Nizzoli, Leonardo oth Tesconi, Maurizio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:67 year:2020 pages:0 https://doi.org/10.1016/j.pmcj.2020.101225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 67 2020 0 |
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towards better social crisis data with hermes: hybrid sensing for emergency management system |
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Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System |
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People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. |
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People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. |
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People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7 × ) and the variety (up to 18 × ) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. |
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Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System |
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